1. Field
This disclosure relates generally to wireless communications, and more specifically to techniques for increasing decoding reliability in an adaptive minimum mean squared error with successive interference cancellation (MMSE/SIC) decoder in a channel-coded multiple-input multiple-output (MIMO) communication system.
2. Related Art
There exist many techniques to share a communications channel among multiple users. Examples of these techniques include code division multiple access (CDMA), orthogonal frequency-division multiple access (OFDMA), time division multiple access (TDMA), and others. Moreover, techniques such as CDMA, OFDMA, and TDMA can be used in conjunction with a Multiple-Input/Multiple-Output (MIMO) system.
In MIMO systems, each of a plurality of data streams is individually encoded, modulated, and combined before being transmitted by multiple antennas. The combined data streams are then received at multiple antennas of a receiver. In some communications systems, such as CDMA, the multiple data streams from multiple users (or even a single user) are superposed on each other and received simultaneously at multiple antennas of the receiver.
Interference is generated from the superposition of these multiple data streams at the receiver. At the receiver, each data stream is separated, extracted, and decoded from the combined signal. This process is generally performed using an adaptive Minimum Mean Squared Error (MMSE) or MMSE-successive interference cancellation (SIC) algorithm. A MMSE algorithm is used for spatial filtering. The MMSE-SIC algorithm detects signal components or data streams one at a time by repeatedly applying the MMSE algorithm. While MMSE filtering can realize low complexity signal detection, the signal output by MMSE filtering suffers from interference by the other signals. To decode a particular data stream for a user, the data stream can be decoded by treating the other data streams as uncorrelated noise. A MMSE-SIC algorithm combines MMSE filtering and SIC to achieve improved Bit Error Rate (BER) performance. According to the SIC technique/algorithm, as each data stream is decoded it is reconstructed and fed back to subtract its contribution to the superposed or aggregated received signal before decoding of subsequent data streams. This technique can improve the utilization of a channel.
However, present techniques for SIC can be impractical to implement. For example, it can be time-consuming and computationally complex to evaluate a relatively large amount of data. This is particularly true in MIMO systems. In addition, SIC techniques can worsen interference when implemented in a high error rate environment. For example, a data stream that is improperly decoded and used in SIC has the potential for increasing the number of errors when decoding the next successive data stream. For these and other reasons, present techniques for SIC are inadequate.